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Mehmet Fatih Amasyali
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2020 – today
- 2024
- [j23]Enes Dedeoglu, Himmet Toprak Kesgin, Mehmet Fatih Amasyali:
A robust optimization method for label noisy datasets based on adaptive threshold: Adaptive-k. Frontiers Comput. Sci. 18(4) (2024) - [j22]Melike Nur Yegin
, Mehmet Fatih Amasyali
Generative diffusion models: A survey of current theoretical developments. Neurocomputing 608: 128373 (2024) - [j21]Gülsüm Yigit, Mehmet Fatih Amasyali:
From text to multimodal: a survey of adversarial example generation in question answering systems. Knowl. Inf. Syst. 66(12): 7165-7204 (2024) - [j20]Himmet Toprak Kesgin
Advancing NLP models with strategic text augmentation: A comprehensive study of augmentation methods and curriculum strategies. Nat. Lang. Process. J. 7: 100071 (2024) - [j19]Gülsüm Yigit
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving. SN Comput. Sci. 5(5): 506 (2024) - [j18]H. Toprak Kesgin
Cyclical Curriculum Learning. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12864-12872 (2024) - [c42]H. Toprak Kesgin, Muzaffer Kaan Yuce, Eren Dogan, M. Egemen Uzun, Atahan Uz, H. Emre Seyrek, Ahmed Zeer, Mehmet Fatih Amasyali:
Introducing cosmosGPT: Monolingual Training for Turkish Language Models. INISTA 2024: 1-6 - [c41]Mehmet Akdis, Mehmet Fatih Amasyali:
Interpolation Based Distributed Learning. SIU 2024: 1-4 - [i15]Himmet Toprak Kesgin, Mehmet Fatih Amasyali:
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling. CoRR abs/2401.01830 (2024) - [i14]Himmet Toprak Kesgin, Mehmet Fatih Amasyali:
Investigating Semi-Supervised Learning Algorithms in Text Datasets. CoRR abs/2401.01843 (2024) - [i13]Himmet Toprak Kesgin, Mehmet Fatih Amasyali:
Advancing NLP Models with Strategic Text Augmentation: A Comprehensive Study of Augmentation Methods and Curriculum Strategies. CoRR abs/2402.09141 (2024) - [i12]Gülsüm Yigit, Mehmet Fatih Amasyali:
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving. CoRR abs/2404.03938 (2024) - [i11]Melike Nur Yegin, Mehmet Fatih Amasyali:
Theoretical research on generative diffusion models: an overview. CoRR abs/2404.09016 (2024) - [i10]Eren Dogan, M. Egemen Uzun, Atahan Uz, H. Emre Seyrek, Ahmed Zeer, Ezgi Sevi, H. Toprak Kesgin, Muzaffer Kaan Yuce, Mehmet Fatih Amasyali:
T\"urk\c{c}e Dil Modellerinin Performans Kar\c{s}{\i}la\c{s}t{\i}rmas{\i} Performance Comparison of Turkish Language Models. CoRR abs/2404.17010 (2024) - [i9]H. Toprak Kesgin, Muzaffer Kaan Yuce, Eren Dogan, M. Egemen Uzun, Atahan Uz, H. Emre Seyrek, Ahmed Zeer, Mehmet Fatih Amasyali:
Introducing cosmosGPT: Monolingual Training for Turkish Language Models. CoRR abs/2404.17336 (2024) - [i8]Farnaz Zeidi, Mehmet Fatih Amasyali, Çigdem Erol:
LegalTurk Optimized BERT for Multi-Label Text Classification and NER. CoRR abs/2407.00648 (2024) - 2023
- [j17]Meltem Aksoy
A comparative analysis of text representation, classification and clustering methods over real project proposals. Int. J. Intell. Comput. Cybern. 16(3): 595-628 (2023) - [j16]Meltem Aksoy
Reviewer Assignment Problem: A Systematic Review of the Literature. J. Artif. Intell. Res. 76: 761-827 (2023) - [j15]Gülsüm Yigit
Enhancing multiple-choice question answering through sequential fine-tuning and Curriculum Learning strategies. Knowl. Inf. Syst. 65(11): 5025-5042 (2023) - [c40]Gülsüm Yigit
Exploring the Benefits of Data Augmentation in Math Word Problem Solving. INISTA 2023: 1-6 - [i7]Meltem Aksoy, Seda Yanik, Mehmet Fatih Amasyali:
Reviewer Assignment Problem: A Systematic Review of the Literature. CoRR abs/2304.00353 (2023) - [i6]Himmet Toprak Kesgin, Muzaffer Kaan Yuce, Mehmet Fatih Amasyali:
Developing and Evaluating Tiny to Medium-Sized Turkish BERT Models. CoRR abs/2307.14134 (2023) - [i5]Gülsüm Yigit, Mehmet Fatih Amasyali:
From Text to Multimodal: A Comprehensive Survey of Adversarial Example Generation in Question Answering Systems. CoRR abs/2312.16156 (2023) - 2022
- [j14]Gülsüm Yigit
Assessing the impact of minor modifications on the interior structure of GRU: GRU1 and GRU2. Concurr. Comput. Pract. Exp. 34(20) (2022) - [j13]Melike Nur Yegin
Training with growing sets: A comparative study. Expert Syst. J. Knowl. Eng. 39(7) (2022) - [j12]Fatma Gumus, Mehmet Fatih Amasyali
Exploiting natural language services: a polarity based black-box attack. Frontiers Comput. Sci. 16(5): 165325 (2022) - [c39]Wadhah Zeyad Tareq, Mehmet Fatih Amasyali:
Merging Reinforcement Learning and Inverse Reinforcement Learning via Auxiliary Reward System. ICAIIC 2022: 292-297 - [c38]Besher Alkurdi, Hasan Yunus Sarioglu, Mehmet Fatih Amasyali:
Semantic Similarity Based Filtering for Turkish Paraphrase Dataset Creation. ICNLSP 2022: 119-127 - [c37]Yusuf Ani, Mehmet Fatih Amasyali:
A General Purpose Turkish CLIP Model (TrCLIP) for Image&Text Retrieval and its Application to E-Commerce. INISTA 2022: 1-6 - [c36]Duygu Akbunar, Batuhan Erdogan, Göksel Biricik, Mehmet Fatih Amasyali:
Determining Functional User Comments of Mobile Applications with Semi-Supervised Learning. SIU 2022: 1-4 - [i4]H. Toprak Kesgin, Mehmet Fatih Amasyali:
Cyclical Curriculum Learning. CoRR abs/2202.05531 (2022) - [i3]H. Toprak Kesgin, Mehmet Fatih Amasyali:
Development and Comparison of Scoring Functions in Curriculum Learning. CoRR abs/2202.06823 (2022) - [i2]Enes Dedeoglu, Himmet Toprak Kesgin, Mehmet Fatih Amasyali:
A Robust Optimization Method for Label Noisy Datasets Based on Adaptive Threshold: Adaptive-k. CoRR abs/2203.14165 (2022) - [i1]M. Safak Bilici, Mehmet Fatih Amasyali:
Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational Bayes. CoRR abs/2205.09391 (2022) - 2021
- [c35]Ahmet Bagci, Mehmet Fatih Amasyali:
Comparison of Turkish Paraphrase Generation Models. INISTA 2021: 1-6 - [c34]Gülsüm Yigit
Simple But Effective GRU Variants. INISTA 2021: 1-6 - [c33]Ahmet Topal
When does Synthetic Data Generation Work? SIU 2021: 1-4 - 2020
- [j11]Abdulkadir Seker, Banu Diri, Halil Arslan
Open Source Software Development Challenges: A Systematic Literature Review on GitHub. Int. J. Open Source Softw. Process. 11(4): 1-26 (2020) - [c32]Mustafa Burak Dilaver, Furkan Çakmak
3D Mapping and Simultaneous Navigation for Multi Micro Aerial Vehicles in Indoor Environments. SIU 2020: 1-4
2010 – 2019
- 2019
- [j10]Salih Marangoz, Mehmet Fatih Amasyali
More scalable solution for multi-robot-multi-target assignment problem. Robotics Auton. Syst. 113: 174-185 (2019) - [j9]Mehmet Fatih Amasyali
Improved Space Forest: A Meta Ensemble Method. IEEE Trans. Cybern. 49(3): 816-826 (2019) - [c31]Fatma Zehra Çetin
The Effects of Corpus Type and Size on the Classification of News. SIU 2019: 1-4 - 2018
- [c30]Ozan Firat Özgül, Mehmet Ulas Çakir, Mehmet Tan
A Fully Unsupervised Framework for Scoring Driving Style. IEEE Conf. on Intelligent Systems 2018: 228-234 - 2017
- [j8]Faruk Bulut
Locally adaptive k parameter selection for nearest neighbor classifier: one nearest cluster. Pattern Anal. Appl. 20(2): 415-425 (2017) - [j7]Muhammet Balcilar
R-SLAM: Resilient localization and mapping in challenging environments. Robotics Auton. Syst. 87: 66-80 (2017) - [j6]Erkan Uslu
An architecture for multi-robot localization and mapping in the Gazebo/Robot Operating System simulation environment. Simul. 93(9): 771-780 (2017) - [c29]Furkan Cakmak
Thermal based exploration for search and rescue robots. INISTA 2017: 113-118 - [c28]Mehmet Fatih Amasyali
Ensemble learning with surrogate splits. SIU 2017: 1-4 - [c27]Furkan Cakmak
Hazmat charts detection on search and rescue league of RoboCup competitions. SIU 2017: 1-4 - [c26]Mustafa Burak Dilaver
Design and implementation of an outdoor line follower robot for RoboCup search and rescue league. SIU 2017: 1-4 - [c25]Numan Keskin, Erkan Uslu
Autonomous mobile robot exploration in negative obstacle environment. SIU 2017: 1-4 - [c24]Salih Marangoz, Ezgi Ekin Ergun, Erkan Uslu
A fast 3D exploration algorithm for autonomous aerial robots. SIU 2017: 1-4 - 2016
- [c23]Muhammet Balcilar
An architecture for multi-robot hector mapping. INISTA 2016: 1-5 - [c22]Bedir Yilmaz, Mehmet Fatih Amasyali
Impact of artificial dataset enlargement on performance of deformable part models. SIU 2016: 193-196 - [c21]Ender Can, Mehmet Fatih Amasyali
Text2arff: A text representation library. SIU 2016: 197-200 - [c20]Meryem Ekinci, M. Said Ozcan, Mehmet Fatih Amasyali
Time effect in sentiment analysis. SIU 2016: 209-212 - [c19]Nihal Altuntas
3 dimensional thermal mapping. SIU 2016: 1201-1204 - [c18]Furkan Cakmak
Deformable part model and deep learning comparison on victim detection. SIU 2016: 1513-1516 - 2015
- [c17]Erkan Uslu
Implementation of frontier-based exploration algorithm for an autonomous robot. INISTA 2015: 1-7 - [c16]Mehmet Fatih Amasyali
Comparison of machine learning methods for the sequence labelling applications. SIU 2015: 503-506 - [c15]Bedir Yilmaz, Muhammet Balcilar
Human victim detection with Deformable Part Models. SIU 2015: 947-950 - [c14]Erkan Uslu
Frontier-based autonomous exploration algorithm implementation. SIU 2015: 1313-1316 - 2014
- [j5]Mehmet Fatih Amasyali, Ayse Demirhan, Mert Bal
Analysis of Changes in Market Shares of Commercial Banks Operating in Turkey Using Computational Intelligence Algorithms. Adv. Artif. Intell. 2014: 649860:1-649860:14 (2014) - [j4]Ugur Simsir, Mehmet Fatih Amasyali
Decision support system for collision avoidance of vessels. Appl. Soft Comput. 25: 369-378 (2014) - [j3]Mehmet Fatih Amasyali
Classifier Ensembles with the Extended Space Forest. IEEE Trans. Knowl. Data Eng. 26(3): 549-562 (2014) - [c13]Furkan Cakmak
Using range and inertia sensors for trajectory and pose estimation. SIU 2014: 506-509 - [c12]Gurkan Sahin, Muhammet Balcilar
Obstacle avoidance with Vector Field Histogram algorithm for search and rescue robots. SIU 2014: 766-769 - 2013
- [c11]Khudaydad Mahmoodi, Muhammet Balcilar
Routing with Dijkstra in Mobile Ad-Hoc Networks. RoboCup 2013: 316-325 - [c10]Cem Agan, Mehmet Fatih Amasyali:
Active learning with committees and the selection of starting sets. SIU 2013: 1-4 - [c9]Abdulkadir Albayrak
Evaluation of robustness of ensemble learners to noisy data. SIU 2013: 1-4 - [c8]Mehmet Fatih Amasyali
A semi-random subspace method for classification ensembles. SIU 2013: 1-4 - [c7]Mahmut Cetin, Mehmet Fatih Amasyali:
Supervised and traditional term weighting methods for sentiment analysis. SIU 2013: 1-4 - [c6]Zeynep Banu Ozger, Mehmet Fatih Amasyali
KNN parameter selection via meta learning. SIU 2013: 1-4 - 2012
- [c5]Mehmet Fatih Amasyali
Word trajectories. SIU 2012: 1-4 - 2011
- [j2]Serkan Ekinci, Ugur Bugra Çelebi, Mert Bal, Mehmet Fatih Amasyali
Predictions of oil/chemical tanker main design parameters using computational intelligence techniques. Appl. Soft Comput. 11(2): 2356-2366 (2011)
2000 – 2009
- 2008
- [b1]Mehmet Fatih Amasyali:
Yeni makine öğrenmesi metotları ve ilaç tasarımına uygulamaları (New machine learning algorithms and applications to drug design). Yıldız Technical University, Turkey, 2008 - [j1]Mehmet Fatih Amasyali
Cline: A New Decision-Tree Family. IEEE Trans. Neural Networks 19(2): 356-363 (2008) - 2007
- [c4]Filiz Türkoglu, Banu Diri, Mehmet Fatih Amasyali:
Author Attribution of Turkish Texts by Feature Mining. ICIC (1) 2007: 1086-1093 - 2006
- [c3]Oguz Altun, Nilgun Dursunoglu, Mehmet Fatih Amasyali
Clustering Application Benchmark. IISWC 2006: 178-181 - [c2]Mehmet Fatih Amasyali, Mert Bal, Ugur Bugra Çelebi, Serkan Ekinci, U. Kasif Boyaci:
Comparison of Different Neural Networks Performances on Motorboat Datasets. ISCIS 2006: 212-220 - [c1]Mehmet Fatih Amasyali, Banu Diri:
Automatic Turkish Text Categorization in Terms of Author, Genre and Gender. NLDB 2006: 221-226
Coauthor Index
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last updated on 2024-12-10 20:52 CET by the dblp team
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